Jason Lemkin led the seed round via SaaStr Fund in unicorn Owner. com, an AI-driven platform transforming how small restaurants operate. Kyle Norton joined soon after and, after a slow start, rapidly grew the company to nearly $100 million ARR within a few years, with scaling growth. Both Jason and Kyle have openly shared insights and experiences from their AI agent implementations, with Kyle now overseeing a 100+ person sales team enhanced by AI, while Jason and Amelia at SaaStr operate over 20 AI agents. **Top 10 Takeaways:** 1. AI agents outperform average sales reps (AEs/SDRs), though not the top performers; this shifts GTM team structures fundamentally. 2. The first AI agent you deploy should be trained and managed personally by the CRO or CMO—agencies or consultants won’t cut it; it requires about 30 days of dedicated work. 3. Focus on one or two tools deeply rather than juggling many vendors; pick an incumbent and a startup to compare. 4. Salesforce remains crucial as a central hub for multiple autonomous AI agents sharing data and insights. 5. The “middle ground” of moderate growth is disappearing—either aim for rapid scale (10x multiples) or settle for slower (15-20%) growth. 6. Prioritize talking to the Forward Deployed Engineers on vendor teams to ensure smooth deployment, as features alone don’t guarantee success. 7. Training each agent rigorously over 30 days is essential; neglecting training causes AI failure. 8. Address your most painful customer journey issues first using AI—test your website incognito, fix what frustrates customers. 9. AI-augmented sales teams are about 3x more productive per rep, leading to higher quotas and growth, not fewer hires. 10. Elite SDRs who manage AI effectively will command salaries 2-3 times higher, expected to deliver 10x output. **Backstory:** SaaStr’s AI pivot began with frustration over costly sales reps quitting without notice amid key events, prompting a shift to AI-driven agents. Starting with one agent in May, SaaStr now runs 20+ agents generating over $1 million revenue, with AI outperforming middle-tier reps. The consequence: mid-pack GTM roles face terminal decline unless they upskill with AI. **Current State:** AI is still early in GTM—today’s "hyper-personalization" in outreach includes only minimal dynamic content, but future AI will leverage comprehensive customer data and interactions to craft highly effective communications rivaling top human effort.

Early AI SDR failures were due to immature LLMs; now stable, failures mostly stem from lack of proper training. **The 30-Day Rule:** Deploying an AI agent entails three phases over 30 days: - Days 1-7: Data ingestion and creating example outputs, - Days 8-21: Daily review and correction, - Days 22-30: Production readiness with minimized errors. Skipping this process leads to poor performance falsely attributed to AI. **Executive Guidance:** CROs and CMOs must personally own AI deployment to avoid obsolescence—it’s no longer viable to rely on agencies or consultants for early adoption. Experienced executives have trained agents themselves before delegating. **Vendor Selection:** Choose one problem to solve first (e. g. , AI SDR, RevOps). Insist on speaking directly with the Forward Deployed Engineer before contracting. Budget roughly $50-100K for the first deployment, focusing on ROI over headcount savings. Avoid overextensive vendor evaluations; two quality options suffice. **Inbound AI:** Quick wins come from AI-enhanced inbound support enabling instant, high-quality interactions with prospects, removing friction from qualification and reducing sales cycle delays—something legacy processes fail at in today’s environment. **Salesforce’s Role:** Salesforce acts as the data hub where multiple AI agents feed information, resolving conflicts and making integrations smoother. Though AgentForce requires more setup, its deep Salesforce integration often gives it an edge. **Productivity Impact:** While AI can boost rep productivity by up to 3x, it doesn’t eliminate the need for headcount due to high growth demands and talent scarcity. High-performing reps managing AI will command significantly higher compensation but must deliver commensurate output gains. **Market Realities:** The “Goldilocks” growth zone (triple-triple-double-double) that once attracted half of VCs now secures funding for only about 10%. Founders must stretch capital, face tougher recruiting, and realistically assess fundability using AI tools like saastr. ai/aivc. **Choosing Your Path:** There is a clear split— - Work exceptionally hard to achieve hyper-growth with intense effort as Kyle Norton and Jason Lemkin exemplify, - Or join slower-growth companies with steadier pace and lifestyle trade-offs. The moderate “middle” scenario largely no longer exists in SaaS GTM. **Top 5 Executive Mistakes with AI GTM Agents:** 1. Overdoing vendor bakeoffs—train only two agents deeply. 2. Outsourcing AI deployment instead of owning it internally. 3. Buying tools without committing to the essential 30-day training. 4. Signing contracts without contact with deployment engineers. 5. Giving AI tools individually to reps without centralized management. **Noteworthy Quotes:** - Jason Lemkin emphasizes: “I am done paying an SDR $150K a year for mediocre outreach then losing them, ” and stresses the necessity for leaders to “roll up your sleeves” in AI or become obsolete. - Kyle Norton highlights a “3x booked revenue per dollar spent per AE” with AI infusion, rapid deployment capabilities, but also the intense personal effort required even with advantages. In sum, AI agents are reshaping B2B GTM strategies, demanding leadership involvement, rigorous training, prudent vendor selection, and acceptance that accelerated growth requires relentless effort and adaptation. The opportunities are immense—but so are the challenges.